Measuring NPS is simply a case of asking the following question:
‘How likely is it that you would recommend [Organisation X/Product Y/Service Z] to a friend or colleague?’
It uses a scale of 0 (not at all likely) to 10 (extremely likely) and based on their responses, customers fall into one of 3 categories:
Promoters respond with a score of 9 or 10
Passives respond with a score of 7 or 8
Detractors respond with a score of 0 to 6
The NPS score is then calculated by ignoring the passive responses and subtracting the % of detractors from the % of promoters.
Designing an NPS Survey – Use Additional Questions
Measuring NPS alone is best for giving you a benchmark score for your customer experience. But how do you improve it? And how do you understand what’s driving your NPS score?
This is where key drivers come in. By understanding your customers’ experiences in more detail, you can establish the most important aspects of the experience that influence that score.
Say for example you’re an online retailer. When a customer has completed a purchase with you, you send them a customer survey. As well as asking how likely they are to recommend your company, you might ask them:
- How easy was it to find the product you were looking for?
- What made you buy from us today [multiple choice]
- How easy were the following parts of your journey? [multiple choice]
In addition, you could also use operational data from things like your website analytics to layer in elements like:
- Time on page
- Referral URL
- Number of pages viewed
- Page load speed
That’s just a snapshot of the kind of data you could pull in. The more you include, the more data points you have to identify what’s really driving your NPS score calculation.
Once you have calculated your NPS you should have significant data points to be able to can run advanced analyses like Key Driver Analysis or multivariate regression to identify your specific ways to improve the customer experience and your NPS scores.